The present invention relates to image sensor signal processing, and more particularly to a method and apparatus for compensating for variations in the sensitivity of image sensors.
Television, in the visible spectrum, is playing an increasingly important role in detection and supervision systems and in military applications such as weapons delivery and surveillance. As the range of electro-optical systems increases, as is the present trend, low-contrast performance becomes of paramount importance due to target contrast degradation resulting from atmospheric scattering. Under light haze viewing conditions with an atmospheric extinction coefficient of 0.4 km.sup.-1, a target of 80 percent contrast is reduced to 1 percent contrast at a range of 10 kilometers.
Manufacturers of silicon diode array vidicons (camera tubes in which a charge-density pattern is formed by photoconduction and stored on an array of photoconductive silicon diodes that are scanned by an electron beam) will not accept specifications on large-area blemishes caused by regional sensitivity differing by less than 5 percent of the nominal sensitivity. FIG. 1 is a photograph of a television screen receiving a signal from an RCA 4532H Silicon vidicon with a fiber optic faceplate. The system is being operated at a high gain. The contrast of the simulated mission targets is 3% at the sensor input. These blemishes are irregular in shape, with sizes ranging up to an appreciable percentage of the raster height. Such local variations are unavoidable in current state of the art silicon sensor technology. As is evident from FIG. 1, when viewing a uniformly illuminated field, these imperfections manifest themselves as coarsely textured, mottled areas on the screen.
Systems tests with high-performance cameras and automatic target trackers have demonstrated that current tracker technology allows performance down to the limit imposed by the sensor mottle which cannot be differentiated from low-contrast signals. Also, such fixed pattern noise has, through psychological testing, been found to significantly impede visual detection. As an example, the average detection time for an object with a lineal extent of 8 percent of the field of view and a contrast of 1 percent was found to increase by a factor of 3.2 with the addition of a 3 percent contrast mottle background. Obviously, these tests were influenced by a number of factors, such as a blemish density, observer motivation, etc. However, the forced response test used does indicate that the observer's task is more difficult with the addition of fixed pattern noise.
To compensate for variations in sensitivity, it is known to arbitrarily divide the sensing surface into a number of small areas, hereafter referred to as elements. A correction coefficient is stored for each element, and the video signal received from each element is processed by the appropriate correction coefficient.
In order to obtain sufficient resolution, the number of elements, and, therefore, the number of correction coefficients, is large. Therefore, in a real time system, the processing of the incoming video signal must be accomplished very quickly.
Furthermore, the compensator must provide sufficient spatial resolution and, should operate independent of scene brightness variations. Another very important parameter in the design of such a compensation device is cost effectiveness. Simply stated, the correction hardward should be affordable by the end user and the benefit realized should be worth the added systems cost.
The technique employed to generate or derive the correction coefficients should suppress or reduce to an acceptable level the effect of thermal noise produced by the sensor and/or its attendant preamplifier. The peak-to-peak thermal noise can easily exceed the blemish amplitude that is being processed out.
One possible video data processing approach is to convert the video data to digital form, operate on the video data with digital techniques and then convert the processed video data back to analog form. However, real time conversion of video data to digital form, is expensive and difficult requiring 8 to 10 bits of gray scale resolution. However, this brute force approach to the problem has been used.
Several other systems are known in the art for compensating for sensitivity variations. An article entitled "A Continuous-Motion Color Film Telecine Using CCD Line Sensors" by Dieter Poetsch in the December 1978 SMPTE Journal, describes a system wherein an incoming signal consisting of a data component and a fixed pattern noise component is multiplied by a function related to the inverse of the fixed noise component to eliminate the fixed noise (pp. 818-819). The article does not detail the manner in which the inverse function is generated. However, it is clear that only the raw video signal is sampled to generate the inverse function (i.e., there is no feedback). Furthermore, it appears that the inverse function is generated from a single sampling, after conversion to a digital format.
The present inventor has determined this approach has several inherent drawbacks. First, since it appears that only one sample of raw video data is obtained, the system does not suppress or reduce the effect of thermal noise. Also the analog-to-digital conversion is expensive. Furthermore, since the output of the multiplier is not sampled to alter the correction values, a high degree of accuracy is not obtainable.
An article entitled "An Experimental Telecine Using A Line-Array CCD Sensor" by Ian Childs et al in the April 1978 SMPTE Journal discloses another method of compensating for sensitivity variations. As discussed on pages 211 and 212, and as illustrated in FIGS. 10-12, the logarithm of the raw video signal is first obtained. From this logarithmic input signal, a logarithmic signal related to the sensitivity variation pattern is subtracted, and the result is passed through an exponential converter. It is not clear from this disclosure where or even whether analog to digital or digital to analog conversions are made. Furthermore, in order to develop the correction data, it appears that only one sample of input data is obtained and the output of the subtractor is not examined to compare results to an ideal. Thus the results may not be as accurate as necessary, and furthermore, there will be no suppression or reduction of the thermal noise level.
An article entitled "Low Contrast Imaging" by Paul Mengers in the October 1978 Electro-Optical Systems Designs describes a method of eliminating fixed pattern noise on page 26. A memory is utilized to store the response of the system to a uniform field input. The pattern is then used as a divisor as each new frame is entered in the processor. The same problems with regard to lack of feedback and no reduction of thermal noise, found in the systems described above, are also present in this system.